Group pattern based electronic dictionary modification and presentation

ABSTRACT

A method and system for using target audience based attributes for modifying an electronic dictionary is provided. The method includes detecting a communication application being enabled via an electronic device. In response, electronic communications of a user are monitored and analyzed with respect to the electronic device and user attributes. Linguistic patterns associated with the electronic communications are determined and with respect to additional electronic communications of said user and a weighted prioritization list of the common terms is generated and electronic dictionary software is modified accordingly. A specified electronic communication currently being entered into the electronic device is monitored and each term of the specified electronic communication is analyzed. In response to the analysis, suggested terms for entering within the specific electronic communication are presented via a graphical user interface of the electronic device.

FIELD

The present invention relates generally to a method for modifyingelectronic dictionary functionality and in particular to a method andassociated system for improving software and memory technologyassociated with monitoring audible and text-based electroniccommunications retrieving audible communications, modifying electronicdictionary software based on audience attributes, and presentingsuggested terms for entering within a specific electronic communication.

BACKGROUND

Accurately monitoring audio to text conversion typically includes aninaccurate process with little flexibility. Modifying text conversionsoftware associated with display interface presentation may include acomplicated process that may be time consuming and require a largeamount of resources. Additionally, presenting predicted termnotifications may require additional human intervention.

SUMMARY

A first aspect of the invention provides a target audience basedelectronic dictionary modification and presentation method comprising:detecting, by a processor of an electronic device via a sensor, acommunication application being enabled via the electronic device;monitoring, by the processor, electronic communications of the user withrespect to the electronic device; first analyzing in real time, by theprocessor, the electronic communications with respect to attributes ofthe user; determining, by said processor based on results of said firstanalyzing, linguistic patterns associated with said electroniccommunications with respect to additional electronic communications ofsaid user and additional target audience users; generating, by theprocessor based on the linguistic patterns, a weighted prioritizationlist of common terms communicated by the user; modifying, by theprocessor based on the weighted prioritization list, electronicdictionary software of the communication application resulting ingeneration of modified electronic dictionary software; monitoring, bythe processor, a specified electronic communication currently beingentered into the electronic device; second analyzing, by the processorexecuting the modified electronic dictionary software, each term of thespecified electronic communication; and presenting based on results ofthe second analyzing, by the processor to the user via a graphical userinterface (GUI) of the electronic device, suggested terms for enteringwithin the specific electronic communication.

A second aspect of the invention provides a computer program product,comprising a computer readable hardware storage device storing acomputer readable program code, the computer readable program codecomprising an algorithm that when executed by a processor of anelectronic device implements a target audience based electronicdictionary modification and presentation method, the method comprising:detecting, by the processor via a sensor, a communication applicationbeing enabled via the electronic device; monitoring, by the processor,electronic communications of the user with respect to the electronicdevice; first analyzing in real time, by the processor, the electroniccommunications with respect to attributes of the user; determining, bythe processor based on results of the first analyzing, linguisticpatterns associated with the electronic communications with respect toadditional electronic communications of the user and additional targetaudience users; generating, by the processor based on the linguisticpatterns, a weighted prioritization list of common terms communicated bythe user; modifying, by the processor based on the weightedprioritization list, electronic dictionary software of the communicationapplication resulting in generation of modified electronic dictionarysoftware; monitoring, by the processor, a specified electroniccommunication currently being entered into the electronic device; secondanalyzing, by the processor executing the modified electronic dictionarysoftware, each term of the specified electronic communication; andpresenting based on results of the second analyzing, by the processor tothe user via a graphical user interface (GUI) of the electronic device,suggested terms for entering within the specific electroniccommunication.

A third aspect of the invention provides an electronic device comprisinga processor coupled to a computer-readable memory unit, the memory unitcomprising instructions that when executed by the processor implements atarget audience based electronic dictionary modification andpresentation method comprising: detecting, by the processor via asensor, a communication application being enabled via the electronicdevice; monitoring, by the processor, electronic communications of theuser with respect to the electronic device; first analyzing in realtime, by the processor, the electronic communications with respect toattributes of the user; determining, by the processor based on resultsof the first analyzing, linguistic patterns associated with theelectronic communications with respect to additional electroniccommunications of the user; generating, by the processor based on thelinguistic patterns, a weighted prioritization list of common termscommunicated by the user and additional target audience users;modifying, by the processor based on the weighted prioritization list,electronic dictionary software of the communication applicationresulting in generation of modified electronic dictionary software;monitoring, by the processor, a specified electronic communicationcurrently being entered into the electronic device; second analyzing, bythe processor executing the modified electronic dictionary software,each term of the specified electronic communication; and presentingbased on results of the second analyzing, by the processor to the uservia a graphical user interface (GUI) of the electronic device, suggestedterms for entering within the specific electronic communication.

The present invention advantageously provides a simple method andassociated system capable of accurately monitoring audio to text forpresentation.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system for improving software and memory technologyassociated with monitoring audible and text-based electroniccommunications retrieving audible communications, modifying electronicdictionary software, and presenting suggested terms for entering withina specific electronic communication, modifying electronic dictionarysoftware, and presenting suggested terms for entering within a specificelectronic communication, in accordance with embodiments of the presentinvention.

FIG. 2 illustrates an algorithm detailing a process flow enabled by thesystem of FIG. 1 for improving software and memory technology associatedwith monitoring audible and text-based electronic communicationsretrieving audible communications, modifying electronic dictionarysoftware, and presenting suggested terms for entering within a specificelectronic communication, in accordance with embodiments of the presentinvention.

FIG. 3 illustrates an internal structural view of the self-learningsoftware/hardware structure of FIG. 1, in accordance with embodiments ofthe present invention.

FIG. 4 illustrates a computer system used by the system of FIG. 1 forimproving software and memory technology associated with retrievingaudible communications, modifying electronic dictionary software, andpresenting suggested terms for entering within a specific electroniccommunication, in accordance with embodiments of the present invention.

FIG. 5 illustrates a cloud computing environment, in accordance withembodiments of the present invention.

FIG. 6 illustrates a set of functional abstraction layers provided bycloud computing environment, in accordance with embodiments of thepresent invention.

DETAILED DESCRIPTION

FIG. 1 illustrates a system 100 for improving software and memorytechnology associated with monitoring audible and text-based electroniccommunications retrieving audible communications, modifying electronicdictionary software, and presenting suggested terms for entering withina specific electronic communication, in accordance with embodiments ofthe present invention. Individual linguistic patterns typically changebased on a specified target audience with respect to transmittingcommunications and an associated context of the communications. Termsselected for communicating with a family member may be different thanterms for use when communicating with a professional colleague.Additionally, a pattern may differ if the communication is associatedwith a single user or members of a group of users. A typicalcommunication system (for communicating via text messaging or email) mayinclude a type ahead electronic dictionary provided with software toolsfor texting while providing recommended words with respect to text-basedcommunications. A typical look ahead electronic dictionary may notinclude terms that relate to specific audience-based terms. Likewise, auser may request to access to specialized audience related terms insteadof a generic device-based list. Therefore, system 100 enables animproved process for generating a customized electronic dictionaryassociated with specified terminology of a specified target audience.

System 100 enables a process for capturing linguistic patterns andassociated word selections (i.e., for audible or written communications)associated with use by an individual or a group of individuals. Theprocess for capturing and analyzing the linguistic patterns andassociated word selections for pattern matching is executed based on anapproval by the user. The approval may additionally include a user'soption to cancel such capturing and analyzing, and thus opt/in andopt/out of capturing and analyzing communications at the user'sdiscretions. Further, any data collected is understood to be intended tobe securely stored and unavailable without authorization. Likewise, anapproval may additionally include a group of user's options to cancelsuch capturing and analyzing, and thus opt/in and opt/out of capturingand analyzing communications at the group of user's discretions.

In response, an electronic dictionary is modified for enabling atype-ahead selection comprising prioritized words. Likewise, warningsare trigged when non-desired words are associated with the electronicdictionary. The aforementioned process is configured to speed up acommunication process by: providing an improved match for a word beingtyped and providing a filter for words that are not relevant.

System 100 is configured to modify recommended type-ahead selectioncapabilities of a device based on a target audience for communicationsas follows:

Linguistic patterns are captured from previous communicationinteractions (via a communication device) with individuals. Words thathave been defined as articles or unusable words are removed from anelectronic dictionary and a weighted prioritization list of words isgenerated based on a communication audience of the individuals.Likewise, a type-ahead list (of words) is supplemented with newlyweighted prioritized words exceeding a pre-configured threshold andunusable words are detected for providing warnings based on thecommunication audience.

System 100 enables the following functionality:

1. Designating a device (comprising an integrated microphone) forcapturing vocal conversations of a user and a text history of a deviceof the user.2. Capturing a vocal conversation and text history of the user.3. Determining linguistic patterns associated with the vocalconversation and text history of the user.4. Generating a weighted prioritization word list based on thedetermined linguistic patterns. The weighted prioritization word list isconfigured to indicate weighted words with respect to an anticipatedaudience. The weighted words are prioritized for usage based on theweighting.5. Receiving a text conversation (initiated by the user on a display ofthe device) via the device.6. Converting the vocal conversation to text format.7. Analyzing the vocal conversation with respect to the textconversation for generation of text suggestions (for typing into a GUIof the device) based on the vocal conversation. The text suggestions aregenerated based on a linguistic style, word preferences, and phrasepatterns. The text suggestions are inputted into the text conversation(via the GUI) based on the analysis of the vocal conversation.Additionally, the text suggestions may be suggestions for avoidingspecified words.8. Suggesting words in a text conversation on the display of the devicebased on the analysis of the vocal conversation.

System 100 of FIG. 1 includes a server hardware device 104 (i.e.,specialized hardware device), an electronic device 105 (including a GUI142), additional user devices 138, and a database 107 (e.g., acloud-based system) interconnected through a network 117. Serverhardware device 104 includes specialized circuitry 127 (that may includespecialized software) and self-learning software code/hardware structure121 (i.e., including self-learning software code). Electronic device 105and additional user devices 138 may include personal devices provided toeach user. Electronic device 105 and additional user devices 138 may beBluetooth enabled to provide connectivity to any type of system.Electronic device 105 includes self-learning software code/hardwarestructure 121 a (e.g., integrated with self-learning softwarecode/hardware structure 121), specialized circuitry 125 (that mayinclude specialized software), audio/video retrieval device 132, sensors110, and code 112 (including configuration code and generatedself-learning software code for transfer to/from server hardware device104). Sensors 110 may include any type of internal or external sensor(or biometric sensor) including, inter alia, ultrasonicthree-dimensional sensor modules, a heart rate monitor, a blood pressuremonitor, a temperature sensor, a pulse rate monitor, an ultrasonicsensor, an optical sensor, a video retrieval device, an audio retrievaldevice, humidity sensors, etc. Server hardware device 104, electronicdevice 105, and database 107 may each may comprise an embedded device.An embedded device is defined herein as a dedicated device or computercomprising a combination of computer hardware and software (fixed incapability or programmable) specifically designed for executing aspecialized function. Programmable embedded computers or devices maycomprise specialized programming interfaces. In one embodiment, serverhardware device 104, electronic device 105, and database 107 may eachcomprise a specialized hardware device comprising specialized(non-generic) hardware and circuitry (i.e., specialized discretenon-generic analog, digital, and logic-based circuitry) for(independently or in combination) executing a process described withrespect to FIGS. 1-6. The specialized discrete non-generic analog,digital, and logic-based circuitry may include proprietary speciallydesigned components (e.g., a specialized integrated circuit, such as forexample an Application Specific Integrated Circuit (ASIC) designed foronly implementing an automated process for improving software and memorytechnology associated with monitoring audible and text-based electroniccommunications retrieving audible communications, modifying electronicdictionary software, and presenting suggested terms for entering withina specific electronic communication. Audio/video retrieval device 132may comprise any type of audio/video device including, inter alia, acamera with gaze point tracking hardware and software, a video camera, astill shot camera, etc. Gaze point tracking comprises a process fortracking motion of an eye by measuring either the point of gaze (i.e., adirection that a user is viewing). Gaze point tracking hardwarecomprises a device for measuring eye positions and eye movement. Network117 may include any type of network including, inter alia, a local areanetwork, (LAN), a wide area network (WAN), the Internet, a wirelessnetwork, etc. Alternatively, network 117 may include an applicationprogramming interface (API).

The following implementation examples describe a system implementingprocesses for improving a type-ahead dictionary based on an audience ofan individual:

A first example is associated with a first user and associated friendsthat frequently use specified words that are unique to a specified groupof individuals. A process is initiated the first user is enabling a textconversation with a second user. The first and second users frequentlyuse specified new words in their written and oral conversations.Therefore, when the first user is texting with friends (including thesecond user) and the system detects that he/she prefers to expresspositive feedback to a friend, the system may automatically recommendspecified words such as “Savage” or “Gucci”. For example, as the firstuser begins typing an “S” or “G” to inform a friend of a positive topicbeing discussed, the system is configured to determine that theaforementioned two words are unique to the audience and presents therecommend specified words “Savage” or “Gucci”.

A second example is associated with a first user that has a new baby inthe family that was just born this year. The first user frequentlydiscusses (via phone conversations) the baby with his wife. Likewise,the first user is traveling on business he uses test messages fordiscussion. Therefore, the system is configured to predict the usage ofthe word “Baby” any time a letter “B” is typed into a text message.Additionally, the first user frequently discusses diapers as well.Therefore, the system is configured to recommend the word “Diapers”anytime the letter D is used. The system comprises a self-learningsystem such that based on a frequency of use of specified words (e.g.,as the baby grow and no longer needs diapers), the predicted word iseliminated from the system.

System 100 enables processes for capturing linguistic patterns,filtering specified words, generating weighted priority words, andsupplementing a type ahead electronic dictionary.

The process for capturing linguistic patterns includes capturing audioand written communications with specified individuals. Associateddevices (e.g., electronic device 105) are registered with system 100 forcapturing audio communications and transmitting text converted contentto system 100 (e.g., server hardware device 104). Verbal communicationsare captured based on a voice print, near field communications withanother device, or analysis of the video feed. Textual content iscaptured from applications used for written communications and specifiedwords are stored within a specialized personal repository linked to aspecified audience.

The process for filtering specified words includes: removing specifiedwords from the specialized personal repository; removing articles from asupplemental list, removing banned words from a GUI; adding wordspreferred words in system; and removing words based on a temporal limit(e.g., a configured attribute).

The process for generating weighted priority words includes prioritizingwords based on a frequency of use and recently used periods associatedwith individuals and groups of individuals. System 100 reviews wordsbased on a targeted audience. For each word, a frequency and recentlyused period is detected via configurable parameter weighting attributessuch that words detected to be used within a very close time periodwindow are assigned a significant boost with respect to a rating.Subsequently, all words are sorted by weighting attributes. The processfor supplementing a type ahead electronic dictionary includes modifyinga priority of a generic electronic type-ahead dictionary such that allbanned words are excluded from a type-ahead recommendation based on anaudience. If a banned word is used without the type-ahead feature, awarning is displayed to the individual initiating the communications.Supplemental words are prioritized with respect generic words based onan audience and a threshold of use with respect to a targeted audience.Social network, corporate directories, and chat members are used toidentify a linkage between multiple individuals and individual clusters(e.g. work vs family).

The following steps associated with electronic device 105 describeimplementation processes for improving an electronic type-aheaddictionary enabled via electronic applications (e.g., texting software):

1. Linguistic patterns used by an individual are captured (via oral andwritten communications) and stored via an enabled communication device(e.g., a cellular phone).2. A supplemental list comprising personalized words is generated. Thepersonalized words are for use and exclusion (in a type ahead electronicdictionary) based on historical communications between a specifiedindividual and an identified group of individuals.3. Specified words are prioritized for supplementing an existingelectronic dictionary.4. Word used are modified by a type-ahead application based oncommunications with the specified individual.5. A supplemental list of personalized words (for an electronicdictionary) is generated.6. Specified terms or words may be removed from or added to thesupplemental list. The specified words or terms may be added or removedbased on frequency of usage, importance, timing of usage, userpreference (e.g., entered via GUI 142), etc.

FIG. 2 illustrates an algorithm detailing a process flow enabled bysystem 100 of FIG. 1 for improving software and memory technologyassociated with monitoring audible and text-based electroniccommunications retrieving audible communications, modifying electronicdictionary software, and presenting suggested terms for entering withina specific electronic communication, in accordance with embodiments ofthe present invention. Each of the steps in the algorithm of FIG. 2 maybe enabled and executed in any order by a computer processor(s)executing computer code. Additionally, each of the steps in thealgorithm of FIG. 2 may be enabled and executed in combination by serverhardware device 104 and electronic device 105. In step 200, acommunication application being enabled is detected via a sensor of anelectronic device. In step 202, electronic communications of a user aremonitored with respect to the electronic device. The electroniccommunications may include, inter alia, audible voice-basedcommunications of the user, visual text-based communications of theuser, audible voice-based communications and visual text-basedcommunications (i.e., a combination) of the user. In step 204, theelectronic communications are analyzed (in real time) with respect toattributes of the user. The analysis may include identifying a group ofusers associated with receiving the electronic communications, andwherein said determining said linguistic patterns comprises analyzingsaid electronic communications with respect to said group of users.

In step 208, linguistic patterns associated with electroniccommunications of the user are determined (e.g., by analyzing theelectronic communications with respect to the group of users).Additionally, specified terms (e.g., comprising differing linguisticpatterns with respect to linguistic preferences of the user and group ofusers) may be removed (based on the linguistic patterns) from theweighted prioritization list.

In step 210, a weighted prioritization list of the common termscommunicated by the user is generated based on the linguistic patterns.Generating the weighted prioritization list of common terms may include,inter alia:

1. Detecting a time period occurring since the user has specified eachterm of the common terms.2. Retrieving the common terms from an audible signal of a visual sourceassociated with the user.3. Retrieving the common terms from audible voice-based communicationsof the user.4. Retrieving the common terms from visual text-based communications ofthe user.5. Detecting a frequency of use for each term of the common terms.

In step 212, electronic dictionary software is modified (based on theweighted prioritization list) resulting in generation of modifiedelectronic dictionary software. In step 214, a specified electroniccommunication currently being entered into the electronic device ismonitored. In step 217, each term of the specified electroniccommunication is analyzed via execution of the modified electronicdictionary software. In step 218, suggested terms for entering withinthe specific electronic communication are presented (in response to theanalysis step 217) via a graphical user interface (GUI) of theelectronic device. In step 220, the weighted prioritization list ofcommon terms is combined with a generic list of standard terms and themodified electronic dictionary software may be modified based on thecombined list resulting in generation of further modified electronicdictionary software. In step 224, self-learning software code forexecuting future electronic dictionary modification and presentationprocesses is generated based on results of steps 218 and 220.

FIG. 3 illustrates an internal structural view of self-learningsoftware/hardware structure 121 and/or self-learning softwarecode/hardware structure 121 a of FIG. 1, in accordance with embodimentsof the present invention. Self-learning software/hardware structure 121includes a sensor interface module 304, an audio video control module310, an analysis and modification module 308, a code generation module314, and communication controllers 302. Sensor interface module 304comprises specialized hardware and software for controlling allfunctions related to sensors 110 of FIG. 1. Audio video control module310 comprises specialized hardware and software for controlling allfunctionality related to audio video retrieval device 132 for retrievingvideo data and implementing the process described with respect to thealgorithm of FIG. 2. Analysis and modification module 308 comprisesspecialized hardware and software for controlling all functions relatedto the analysis and modification steps of FIG. 2. Code generation module314 comprises specialized hardware and software for controlling allfunctions related to generating machine learning feedback for generatingself-learning software code for executing future electronic dictionarymodification and presentation processes. Communication controllers 302are enabled for controlling all communications between sensor interfacemodule 304, audio video control module 310, analysis and modificationmodule 308, and code generation module 314.

FIG. 4 illustrates a computer system 90 (e.g., electronic device 105and/or server hardware device 104 of FIG. 1) used by or comprised by thesystem of FIG. 1 for improving software and memory technology associatedwith monitoring audible and text-based electronic communicationsretrieving audible communications, modifying electronic dictionarysoftware, and presenting suggested terms for entering within a specificelectronic communication, in accordance with embodiments of the presentinvention.

Aspects of the present invention may take the form of an entirelyhardware embodiment, an entirely software embodiment (includingfirmware, resident software, micro-code, etc.) or an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit,” “module,” or “system.”

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing apparatus receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, device(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general-purpose computer, special purpose computer, orother programmable data processing device to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing device, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing device, and/or other devicesto function in a particular manner, such that the computer readablestorage medium having instructions stored therein comprises an articleof manufacture including instructions which implement aspects of thefunction/act specified in the flowchart and/or block diagram block orblocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing device, or other device tocause a series of operational steps to be performed on the computer,other programmable device or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable device, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The computer system 90 illustrated in FIG. 4 includes a processor 91, aninput device 92 coupled to the processor 91, an output device 93 coupledto the processor 91, and memory devices 94 and 95 each coupled to theprocessor 91. The input device 92 may be, inter alia, a keyboard, amouse, a camera, a touchscreen, etc. The output device 93 may be, interalia, a printer, a plotter, a computer screen, a magnetic tape, aremovable hard disk, a floppy disk, etc. The memory devices 94 and 95may be, inter alia, a hard disk, a floppy disk, a magnetic tape, anoptical storage such as a compact disc (CD) or a digital video disc(DVD), a dynamic random-access memory (DRAM), a read-only memory (ROM),etc. The memory device 95 includes a computer code 97. The computer code97 includes algorithms (e.g., the algorithm of FIG. 2) for improvingsoftware and memory technology associated with monitoring audible andtext-based electronic communications retrieving audible communications,modifying electronic dictionary software, and presenting suggested termsfor entering within a specific electronic communication. The processor91 executes the computer code 97. The memory device 94 includes inputdata 96. The input data 96 includes input required by the computer code97. The output device 93 displays output from the computer code 97.Either or both memory devices 94 and 95 (or one or more additionalmemory devices Such as read only memory device 96) may includealgorithms (e.g., the algorithm of FIG. 2) and may be used as a computerusable medium (or a computer readable medium or a program storagedevice) having a computer readable program code embodied therein and/orhaving other data stored therein, wherein the computer readable programcode includes the computer code 97. Generally, a computer programproduct (or, alternatively, an article of manufacture) of the computersystem 90 may include the computer usable medium (or the program storagedevice).

In some embodiments, rather than being stored and accessed from a harddrive, optical disc or other writeable, rewriteable, or removablehardware memory device 95, stored computer program code 84 (e.g.,including algorithms) may be stored on a static, nonremovable, read-onlystorage medium such as a Read-Only Memory (ROM) device 85, or may beaccessed by processor 91 directly from such a static, nonremovable,read-only medium 85. Similarly, in some embodiments, stored computerprogram code 97 may be stored as computer-readable firmware 85, or maybe accessed by processor 91 directly from such firmware 85, rather thanfrom a more dynamic or removable hardware data-storage device 95, suchas a hard drive or optical disc.

Still yet, any of the components of the present invention could becreated, integrated, hosted, maintained, deployed, managed, serviced,etc. by a service supplier who offers to improve software and memorytechnology associated with monitoring audible and text-based electroniccommunications retrieving audible communications, modifying electronicdictionary software, and presenting suggested terms for entering withina specific electronic communication. Thus, the present inventiondiscloses a process for deploying, creating, integrating, hosting,maintaining, and/or integrating computing infrastructure, includingintegrating computer-readable code into the computer system 90, whereinthe code in combination with the computer system 90 is capable ofperforming a method for enabling a process for improving software andmemory technology associated with monitoring audible and text-basedelectronic communications retrieving audible communications, modifyingelectronic dictionary software, and presenting suggested terms forentering within a specific electronic communication. In anotherembodiment, the invention provides a business method that performs theprocess steps of the invention on a subscription, advertising, and/orfee basis. That is, a service supplier, such as a Solution Integrator,could offer to enable a process for improving software and memorytechnology associated with monitoring audible and text-based electroniccommunications retrieving audible communications, modifying electronicdictionary software, and presenting suggested terms for entering withina specific electronic communication. In this case, the service suppliercan create, maintain, support, etc. a computer infrastructure thatperforms the process steps of the invention for one or more customers.In return, the service supplier can receive payment from the customer(s)under a subscription and/or fee agreement and/or the service suppliercan receive payment from the sale of advertising content to one or morethird parties.

While FIG. 4 shows the computer system 90 as a configuration of hardwareand software, any configuration of hardware and software, as would beknown to a person of ordinary skill in the art, may be utilized for thepurposes stated supra in conjunction with the computer system 90 of FIG.4. For example, the memory devices 94 and 95 may be portions of a singlememory device rather than separate memory devices.

Cloud Computing Environment

It is to be understood that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported, providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure that includes anetwork of interconnected nodes.

Referring now to FIG. 5, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 includes one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A, 54B,54C and 54N shown in FIG. 5 are intended to be illustrative only andthat computing nodes 10 and cloud computing environment 50 cancommunicate with any type of computerized device over any type ofnetwork and/or network addressable connection (e.g., using a webbrowser).

Referring now to FIG. 6, a set of functional abstraction layers providedby cloud computing environment 50 (see FIG. 5) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 6 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may include applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 101 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 102; software development and lifecycle management 103;virtual classroom education delivery 104; data analytics processing 105;transaction processing 106; and for improving software and memorytechnology associated with monitoring audible and text-based electroniccommunications retrieving audible communications, modifying electronicdictionary software, and presenting suggested terms for entering withina specific electronic communication 107.

While embodiments of the present invention have been described hereinfor purposes of illustration, many modifications and changes will becomeapparent to those skilled in the art. Accordingly, the appended claimsare intended to encompass all such modifications and changes as fallwithin the true spirit and scope of this invention.

What is claimed is:
 1. A target audience based electronic dictionarymodification and presentation method comprising: detecting, by aprocessor of an electronic device via a sensor, a communicationapplication being enabled via said electronic device; monitoring, bysaid processor, electronic communications of said user with respect tosaid electronic device; first analyzing in real time, by said processor,said electronic communications with respect to attributes of said user;determining, by said processor based on results of said first analyzing,linguistic patterns associated with said electronic communications withrespect to additional electronic communications of said user andadditional target audience users; generating, by said processor based onsaid linguistic patterns, a weighted prioritization list of common termscommunicated by said user; modifying, by said processor based on saidweighted prioritization list, electronic dictionary software of saidcommunication application resulting in generation of modified electronicdictionary software; monitoring, by said processor, a specifiedelectronic communication currently being entered into said electronicdevice; second analyzing, by said processor executing said modifiedelectronic dictionary software, each term of said specified electroniccommunication; and presenting based on results of said second analyzing,by said processor to said user via a graphical user interface (GUI) ofsaid electronic device, suggested terms for entering within saidspecific electronic communication.
 2. The method of claim 1, whereinsaid electronic communications comprise audible voice-basedcommunications of said user.
 3. The method of claim 1, wherein saidelectronic communications comprise visual text-based communications ofsaid user.
 4. The method of claim 1, wherein said electroniccommunications comprise audible voice-based communications and visualtext-based communications of said user.
 5. The method of claim 1,wherein said generating said weighted prioritization list comprises:retrieving said common terms from an audible signal of a visual sourceassociated with said user.
 6. The method of claim 1, wherein saidgenerating said weighted prioritization list comprises: retrieving saidcommon terms from audible voice-based communications of said user. 7.The method of claim 1, wherein said generating said weightedprioritization list comprises: retrieving said common terms from visualtext-based communications of said user.
 8. The method of claim 1,wherein said first analyzing comprises; identifying a group of usersassociated with receiving said electronic communications, and whereinsaid determining said linguistic patterns comprises analyzing saidelectronic communications with respect to said group of users.
 9. Themethod of claim 8, further comprising: removing, by said processor basedon said linguistic patterns, specified terms from said weightedprioritization list of common terms, wherein said specified termscomprise terms determined to comprise differing linguistic patterns withrespect to linguistic preferences of said user and said group of users;and modifying, by said processor based on said weighted prioritizationlist, said modified electronic dictionary software resulting ingeneration of further modified electronic dictionary software.
 10. Themethod of claim 1, wherein said generating said weighted prioritizationlist of common terms comprises: detecting a frequency of use for eachterm of said common terms.
 11. The method of claim 1, wherein saidgenerating said weighted prioritization list of common terms comprises:detecting a time period occurring since said user has specified eachterm of said common terms.
 12. The method of claim 1, furthercomprising: combining, by said processor, said weighted prioritizationlist of common terms with a generic list of standard terms; andmodifying, by said processor based on said combining, said modifiedelectronic dictionary software.
 13. The method of claim 1, furthercomprising: generating, by said processor based on results of saidsecond analyzing and said presenting, self-learning software code forexecuting future electronic dictionary modification and presentationprocesses.
 14. The method of claim 1, further comprising: providing atleast one support service for at least one of creating, integrating,hosting, maintaining, and deploying computer-readable code in thecontrol hardware, said code being executed by the computer processor toimplement: said detecting, said monitoring said electroniccommunications, said first analyzing, said determining, said generating,said modifying said specified electronic communication, said monitoring,said second analyzing, and said presenting.
 15. A computer programproduct, comprising a computer readable hardware storage device storinga computer readable program code, said computer readable program codecomprising an algorithm that when executed by a processor of anelectronic device implements a target audience based electronicdictionary modification and presentation method, said method comprising:detecting, by said processor via a sensor, a communication applicationbeing enabled via said electronic device; monitoring, by said processor,electronic communications of said user with respect to said electronicdevice; first analyzing in real time, by said processor, said electroniccommunications with respect to attributes of said user; determining, bysaid processor based on results of said first analyzing, linguisticpatterns associated with said electronic communications with respect toadditional electronic communications of said user and additional targetaudience users; generating, by said processor based on said linguisticpatterns, a weighted prioritization list of common terms communicated bysaid user; modifying, by said processor based on said weightedprioritization list, electronic dictionary software of saidcommunication application resulting in generation of modified electronicdictionary software; monitoring, by said processor, a specifiedelectronic communication currently being entered into said electronicdevice; second analyzing, by said processor executing said modifiedelectronic dictionary software, each term of said specified electroniccommunication; and presenting based on results of said second analyzing,by said processor to said user via a graphical user interface (GUI) ofsaid electronic device, suggested terms for entering within saidspecific electronic communication.
 16. The computer program product ofclaim 15, wherein said electronic communications comprise audiblevoice-based communications of said user.
 17. The computer programproduct of claim 15, wherein said electronic communications comprisevisual text-based communications of said user.
 18. The computer programproduct of claim 15, wherein said electronic communications compriseaudible voice-based communications and visual text-based communicationsof said user.
 19. The computer program product of claim 15, wherein saidgenerating said weighted prioritization list comprises: retrieving saidcommon terms from an audible signal of a visual source associated withsaid user.
 20. An electronic device comprising a processor coupled to acomputer-readable memory unit, said memory unit comprising instructionsthat when executed by the processor implements a target audience basedelectronic dictionary modification and presentation method comprising:detecting, by said processor via a sensor, a communication applicationbeing enabled via said electronic device; monitoring, by said processor,electronic communications of said user with respect to said electronicdevice; first analyzing in real time, by said processor, said electroniccommunications with respect to attributes of said user; determining, bysaid processor based on results of said first analyzing, linguisticpatterns associated with said electronic communications with respect toadditional electronic communications of said user and additional targetaudience users; generating, by said processor based on said linguisticpatterns, a weighted prioritization list of common terms communicated bysaid user; modifying, by said processor based on said weightedprioritization list, electronic dictionary software of saidcommunication application resulting in generation of modified electronicdictionary software; monitoring, by said processor, a specifiedelectronic communication currently being entered into said electronicdevice; second analyzing, by said processor executing said modifiedelectronic dictionary software, each term of said specified electroniccommunication; and presenting based on results of said second analyzing,by said processor to said user via a graphical user interface (GUI) ofsaid electronic device, suggested terms for entering within saidspecific electronic communication.